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Model Report


Last Revision Date: 07/02/2010 View as PDF
General Information Back to Top
Model Abbreviated Name:

Model Extended Name:

Model Overview/Abstract:
OncoLogicTM - A Computer System to Evaluate the Carcinogenic Potential of Chemicals
OncoLogicTM is a software program that evaluates the likelihood that a chemical may cause cancer. OncoLogicTM has been peer reviewed and is being released by EPA at no cost, to be available to any researcher or organization wishing to evaluate cancer potential of chemicals. This expert system is a computer program that mimics the judgment of experts by following sets of knowledge rules that are based on studies of how chemicals cause cancer in animals and humans. An expert system, like OncoLogicTM, asks for chemical and use information from the user and following the knowledge rules incorporated into the system, uses the responses to construct an estimation of the most likely results. Currently OncoLogicTM has subsystems that can evaluate fibers, metals, polymers, and more than 48 classes of organic chemicals.
Keywords: Carcinogenicity, cancer, SAR, Structure Activity Relationships, Expert System
Model Technical Contact Information:
Agency Contact:
Dr. Yintak Woo, U.S. EPA
Office of Chemical Safety and Pollution Prevention
Risk Assessment Division
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, NW
Washington, DC 20460-0001
Phone: 202-564-7603
email: woo.yintak@epa.gov
Model Homepage: http://www.epa.gov/oppt/sf/pubs/oncologic.htm
Substantive Changes from Prior Version: Upgraded the user interface and model platform to be more user friendly and compatible with newer operating systems and hardware.
Plans for further model development: Future plans to enhance the expert rules and expand organic chemical classes

User Information Back to Top
Technical Requirements
Computer Hardware
Minimum requirements are an IBM-compatible computer with an 80386 or 80286 processor and 640 KB RAM. At least 512 to 550 KB RAM must be free for acceptable performance, and expanded memory will improve performance.
Compatible Operating Systems
Microsoft Windows 95 or later (including 98, ME, NT, XP and Vista).
Other Software Required to Run the Model
Download Information
Included in the installer are the Quick Start Tutorial and the OncoLogicTM User Guide, which are also posted below for separate download.
Using the Model
Basic Model Inputs
Inputs are chemical class dependant. May include: structure (including subunits present), physical/chemical properties (stability, etc.), biological and mechanistic information, as well as possible routes of exposure
Basic Model Outputs
The output from OncoLogicTM is a justification report consisting of two parts: a summary of the evaluation and a line of reasoning (justification) of how the final conclusions were derived. Within the summary section, a final level of concern is stated along with any other messages that merit special attention. The concern levels used by the OncoLogicTM system are qualitative terms used by the U.S. EPA Structure Activity Team (SAT) for ranking the hazard levels of chemicals. The specific terms in order from highest concern to lowest concern are: HIGH, HIGH-MODERATE, MODERATE, LOW-MODERATE, MARGINAL, LOW. The line of reasoning part of the justification report keeps track of the rules that are used to arrive at a level of concern. The line of reasoning is specific to each evaluation and represents the actual rules used for the particular compound. The line of reasoning section also will draw attention to special considerations flagged for the compound, but in further detail than the summary section.
User Support
User's Guide Available?
OncoLogicTM Users Manual (2010). Risk Assessment Division (7403), Office of Pollution Prevention and Toxics, U.S. Environmental Protection Agency, 1200 Pennsylvania Ave., N.W., Washington, DC 20460. Available at: http://www.epa.gov/oppt/sf/pubs/UserManual.pdf
Other User Documents
  • OncoLogicTM Quick Start Tutorial (PDF) (50 pp, 1.15MB)
  • OncoLogicTM: Frequently Asked Questions (PDF) (6 pp, 260 KB)
  • Running the model(PDF) (10 pp, 144K)
  • Interpreting results (PDF) (1 p, 46K)
  • OncoLogicTM Cancer Assessment Presentation for SF Program (PDF) (51 pp, 332 KB)
Availability of User Support
Yes - see agency contact information
User Qualifications
OncoLogicTM users should be familiar with organic chemistry and know certain characteristics of the chemical of interest including: structure (including subunits present), physical/chemical properties (stability, etc.), biological and mechanistic information, as well as possible routes of exposure. Users are encouraged to seek assistance from chemists, carcinogenesis experts, and other environmental health specialists when using OncoLogicTM

Model Science Back to Top
Problem Identification
Structure Activity Relationship analysis is a technique routinely used by EPA to evaluate chemicals being reviewed by the U.S. Environmental Protection Agency (EPA) in response to Pre-Manufacture Notices mandated by Section 5 of the Toxic Substances Control Act (TSCA). Additional uses of SAR and OncoLogicTM by OPPT staff in various Prioritization Studies include; OPPT: Section 4, High Production Volume Program, Moderate Production Volume Chemicals, Design for the Environment, and EPA Green Chemistry, OPP: Pesticide Inerts, OSWER: Polycyclic Aromatic Hydrocarbons in hazardous waste sites, OW: Drinking Water Disinfection Byproducts (DBP) , OAR: Hazardous Air Pollutants (HAPs).
Summary of Model Structure and Methods
OncoLogicTM asks for chemical and use information from the user and following the knowledge rules incorporated into the system, uses the responses to construct an estimation of the most likely results. OncoLogicTM uses two different methods to predict potential carcinogenicity, structural (SAR) analysis, and functional analysis. Structural analysis makes use of mechanism-based SAR analysis, which involves comparison with structurally related compounds with known carcinogenic activity, identification of structural moieties or fragments that may contribute to carcinogenic activity through a perceived or postulated mechanism, and evaluation of the modifying role of the remainder of the molecule to which the structural moiety/fragment is attached. Cancer data from the following sources were used to develop the knowledge rules:
  1. A six-volume series of monographs entitled ‘Chemical Induction of Cancer’ [1-5];
  2. International Agency for Research on Cancer (IARC) monograph series;
  3. U.S. National Cancer Institute (NCI)/National Toxicology Program (NTP) technical report series;
  4. U.S. Public Health Service publication series 149 entitled ‘Survey of Compounds Which Have Been Tested for Carcinogenic Activity’;
  5. The Carcinogenic Potency Database (CPDB); and
  6. Mon-classified chemical industry and U.S. EPA research data
Model Evaluation
OncoLogicTM was peer reviewed at the developmental stage by external domain experts and, after completion of versions 2.0 and 4.0, by two international peer review panels of domain experts. In addition, the scientific basis of the rule packages for a number of classes of chemicals were published in peer-reviewed open literature. The OncoLogicTM team also participated in an international prospective predictive exercise sponsored by NTP to evaluate the capabilities of various methods to predict the outcome of cancer bioassays several years before the studies were completed. In the first exercise, focusing on 1 of 8 aromatic amines, OncoLogicTM achieved a high degree of accuracy. In the second exercise on 30 chemicals of diverse structure, the OncoLogicTM approach was rated as one of the best performers (Benigni, R, Zito, R: The 2nd NTP Comparative Exercise on the Prediction of Rodent Carcinogenicity: Definitive Results, Mutat. Res. 566, 49, 2004). In addition, a separate external validation of OncoLogicTM performed by the FDA Food Additives Division (Mayer et al., SAR analysis tool: validation and applicability in predicting carcinogens. Regul. Toxicol. Pharmacol. 50: 50, 2008) showed accuracy of 91% overall for all chemicals of interest, and 96% accuracy for those carcinogens of highest concern within the validation exercise.
Key Limitations to Model Scope
The OncoLogicTM Program is only appropriate for those chemicals that fall within a defined OncoLogicTM class (48 classes of organics, metal, fibers, and polymers). Chemicals outside the class definitions can not be evaluated using OncoLogicTM.
Case Studies
Woo, Y.-T., Lai, D., McLain, J.L, Manibusan, M.K., and Dellarco, V.: Use of mechanism-based structure-activity relationship analysis in carcinogenic potential ranking for drinking water disinfection by-products, Environ. Health Persp. 110 (Suppl. 1): 75-87, 2002.

Weinberg, HS, Krasner, SW, Richardson SD, Thruston, AD Jr.: The Occurrence of Disinfection By-Products (DBPs) of Health Concern in Drinking Water: Results of a Nationwide DBP Occurrence Study. EPA/600/R-02/068, National Exposure Research Laboratory, Office of Research and Development, U.S.EPA, Athens, GA, 2002.

Plewa, M..J., Wagner, E.D., Richardson, S.D., Thruston, Jr., A.D., Woo, Y.T., and McKaague, A.B.: Chemical and biological characterization of newly discovered iodoacid drinking water disinfection byproducts. Environ. Sci. Technol. 38: 4713-4722, 2004.

Muellner, M, Wagner, E, McCalla, K, Richardson, S.D, Woo, Y.T, and Plewa, M.: Haloacetonitriles vs. Regulated Haloacetic Acids: Are Nitrogen-Containing DBPS More Toxic? Environ. Sci. Technol. 41: 645-651, 2007.

Plewa, M..J., Muellner, M.G., Richardson, S.D., Fasano, F., Buettner, K.M., Woo, Y.T., McKaague, A.B, and Wagner, E.D.: Occurrence, Synthesis, and Mammalian Cell Cytotoxicity and Genotoxicity of Haloacetamides: An Emerging Class of Nitrogeneous Drinking Water Disinfection Byproducts. Environ. Sci. Technol. 42: 955-961, 2008.

Benigni, R., and Zito, R.: The second NTP comparative exercise on the prediction of rodent carcinogenicity: definitive results. Mutatation Research 566, 49-63, 2004

Woo, Y., and Lai, D: OncoLogic: A Mechanism-Based Expert System for Predicting the Carcinogenic Potential of Chemicals. In: Predictive Toxicology, C. Helma, ed., Taylor and Francis, 2005, pp.385-413.

Mayer, J., Cheeseman, M.A., and Twaroski, M.L: Structure Activity Relationship Analysis Tools: Validation and Applicability in Predicting Carcinogens. Regulatory Toxicology Pharmacology 50: 50-58, 2008.

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